|
gptkbp:instance_of
|
gptkb:organ
|
|
gptkbp:automated
|
gptkb:Azure_Functions
gptkb:Azure_Logic_Apps
gptkb:Git_Hub_Actions
|
|
gptkbp:can_be_used_for
|
gptkb:Hyperparameter_Tuning
Real-time Inference
Batch Inference
|
|
gptkbp:developed_by
|
gptkb:Microsoft
|
|
gptkbp:enables
|
gptkb:collaboration
Version Control
Reproducibility
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Azure ML Pipelines
|
|
gptkbp:integrates_with
|
gptkb:Azure_Data_Lake
gptkb:Azure_Blob_Storage
gptkb:Azure_Dev_Ops
|
|
gptkbp:is_accessible_by
|
gptkb:Azure_Portal
gptkb:CLI
REST API
|
|
gptkbp:is_available_on
|
gptkb:Azure_Marketplace
|
|
gptkbp:is_compatible_with
|
gptkb:Jupyter_Notebooks
gptkb:Power_BI
gptkb:Visual_Studio_Code
|
|
gptkbp:is_part_of
|
gptkb:Azure_Machine_Learning
|
|
gptkbp:is_scalable
|
High Throughput
Large Datasets
Multiple Users
|
|
gptkbp:is_used_by
|
Data Analysts
Data Scientists
Machine Learning Engineers
|
|
gptkbp:offers
|
Model Management
Experiment Tracking
Pipeline Orchestration
|
|
gptkbp:provides
|
gptkb:Data_Science_Workbench
gptkb:machine_learning
Monitoring Tools
Security Features
Visual Interface
|
|
gptkbp:supports
|
gptkb:Kubernetes
gptkb:Tensor_Flow
gptkb:Identity_and_Access_Management
gptkb:Py_Torch
gptkb:MLflow
gptkb:Scikit-learn
Data Encryption
Experimentation
Data Validation
Model Training
Feature Engineering
Model Deployment
Audit Logs
Data Preparation
Custom Docker Containers
Data Drift Detection
Model Drift Detection
|
|
gptkbp:uses
|
gptkb:R_SDK
Python SDK
|
|
gptkbp:bfsParent
|
gptkb:Microsoft_cloud_services
|
|
gptkbp:bfsLayer
|
6
|